Proximal measurements of solar-induced fluorescence and surface reflectance capture seasonal productivity and drought stress dynamics in semiarid grassland ecosystem

Remote sensing approaches have been widely used to monitor gross primary productivity (GPP), but typically reflect changes in ecosystem state, e.g., green leaf area, rather than physiological function, e.g., light use efficiency (LUE). Here, we evaluate proximal measurements of the near-infrared reflectance of vegetation index multiplied by photosynthetically active radiation (NIR _v P), solar-induced fluorescence (SIF), and photochemical reflectance index (PRI) and their sensitivity to GPP and LUE at a semiarid mixed grassland in southeastern Arizona during the 2019 and 2020 growing seasons. Notably, the 2020 season was characterized by a wet spring followed by an extreme summer drought, which drove a shift in dominance from shallow-rooted grasses to deeper-rooted shrubs. Across both years, NIR _v P (R² = 0.79) and SIF (R² = 0.77) performed similarly in tracking biweekly GPP. However, during the 2020 wet-to-drought transition, SIF (R² = 0.82, bias = 0%) and PRI (R² = 0.80, bias = 20%) outperformed NIR _v P (R² = 0.65, bias = 19%) in tracking GPP, likely due to their sensitivity to changes in ecosystem LUE. Supporting this finding, both SIF normalized by total surface reflectance (SIF _r ) and PRI were found to more closely track biweekly LUE (R² = 0.69 and 0.81, respectively), with lower bias (4% and 14%, respectively) compared to NIR _v P (R² = 0.61; bias = 17%). Overall, our results demonstrate that SIF, NIR _v P, and PRI provide complementary insights into the drought response of a semiarid grassland ecosystem. Integrating these metrics could significantly enhance our capacity to monitor and mechanistically model the complex ecophysiological responses of semiarid ecosystems to drought stress.